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aloobun/CosmicBun-8B
CosmicBun-8B is a text generation model from aloobun. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
This is a merge of pre-trained language models created using mergekit.
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From the Hugging Face model README
This is a merge of pre-trained language models created using mergekit.
This model was merged using the DARE TIES merge method using Locutusque/llama-3-neural-chat-v1-8b as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
base_model: Locutusque/llama-3-neural-chat-v1-8b
dtype: bfloat16
merge_method: dare_ties
parameters:
int8_mask: 1.0
normalize: 0.0
slices:
- sources:
- layer_range: [0, 4]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.6
- layer_range: [0, 4]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.6
weight: 0.5
- layer_range: [0, 4]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.5
- sources:
- layer_range: [4, 8]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.8
weight: 0.1
- layer_range: [4, 8]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 1.0
weight: 0.2
- layer_range: [4, 8]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.7
- sources:
- layer_range: [8, 12]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.7
weight: 0.1
- layer_range: [8, 12]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.7
weight: 0.2
- layer_range: [8, 12]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.7
weight: 0.6
- sources:
- layer_range: [12, 16]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.9
weight: 0.2
- layer_range: [12, 16]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.6
weight: 0.6
- layer_range: [12, 16]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.7
weight: 0.3
- sources:
- layer_range: [16, 20]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.2
- layer_range: [16, 20]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 1.0
weight: 0.2
- layer_range: [16, 20]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.9
weight: 0.4
- sources:
- layer_range: [20, 24]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.7
weight: 0.2
- layer_range: [20, 24]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.9
weight: 0.3
- layer_range: [20, 24]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.4
- sources:
- layer_range: [24, 28]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.4
- layer_range: [24, 28]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.8
weight: 0.2
- layer_range: [24, 28]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.9
weight: 0.4
- sources:
- layer_range: [28, 32]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.3
- layer_range: [28, 32]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.9
weight: 0.2
- layer_range: [28, 32]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.3
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 68.81 |
| AI2 Reasoning Challenge (25-Shot) | 61.86 |
| HellaSwag (10-Shot) | 84.29 |
| MMLU (5-Shot) | 65.53 |
| TruthfulQA (0-shot) | 54.08 |
| Winogrande (5-shot) | 78.85 |
| GSM8k (5-shot) | 68.23 |